In general, in stores, sales data that have been registered and processed by sales data processing apparatus such as electronic cash registers (ECRs) or point of sale (POS) terminals are analyzed and attributes (shopping frequencies, repeat rates, genders, age groups, etc.) of customers (purchasers) are also analyzed. For example, shopping frequencies, repeat rates, genders, age groups, etc. of customers are analyzed by identifying the customers (member IDs) and recording shopping history data on the basis of card data that are read from their member's cards that were issued in advance. However, this customer analysis method using member's cards may have problems that the issuance of member's cards requires time, labor, and cost, it may become necessary to increase the membership joining ratio, and non-member customers are not involved in a customer analysis.
A technique for addressing the above is known in which a camera for imaging the face of each customer is provided, a customer is identified by extracting features of his or her face from an image taken by the camera and comparing them with the contents (face feature point data) of a customer database, and customer data (name, address, telephone number, etc.) that is correlated with the identified customer is read from the customer database (refer to JP-A-2001-325433).
However, the technique of JP-A-2001-325433 still has a problem that even if the face of a customer is shot with the camera, proper features of the face need not always be extracted from a face image taken at a high probability, that is, the reliability of face recognition is not sufficiently high.